Comparison of radar-based human detection techniques

被引：0
|
作者：
Gurbuz, Sevgi Zubeyde [1 ]
Melvin, William L. [2 ]
Williams, Douglas B. [1 ]
机构：
[1] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
[2] Georgia Inst Technol, George Tech Res Inst, Atlanta, GA 30332 USA
来源：
CONFERENCE RECORD OF THE FORTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1-5 | 2007年
关键词：
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Radar offers unique advantages over other sensors in the human detection problem, such as remote operation during virtually all weather and lighting conditions. Many radar-based human detection systems today employ Fourier analysis, such as spectrograms. However, spectrograms perform poorly in high clutter environments. Also, an inherent SNR loss is caused by the implicit assumption of linear target phase. In this paper, human modeling is used to derive a more accurate non-linear approximation to the true non-linear target phase and the liklihood ratio is optimized over unknown parameters to enhance detection performance. Performance Is compared both analytically and through MATLAB simulations.
引用
收藏
页码：2199 / +
页数：2
相关论文
共 50 条
  • [31] Enhancing Radar-Based Stroke Detection: A Novel Approach Integrating Huygens' Principle and Deep Learning Techniques
    Movafagh, Moein
    Ghavami, Navid
    Tiberi, Gianluigi
    Taghipour-Gorjikolaie, Mehran
    Cecchi, Paolo
    Cosottini, Mirco
    Dudley, Sandra
    Ghavami, Mohammad
    IEEE SENSORS JOURNAL, 2024, 24 (21) : 36085 - 36098
  • [32] Operational Application of Optical Flow Techniques to Radar-Based Rainfall Nowcasting
    Woo, Wang-chun
    Wong, Wai-kin
    ATMOSPHERE, 2017, 8 (03)
  • [33] Radar-Based Pedestrian and Vehicle Detection and Identification for Driving Assistance
    Viadero-Monasterio, Fernando
    Alonso-Renteria, Luciano
    Perez-Oria, Juan
    Viadero-Rueda, Fernando
    VEHICLES, 2024, 6 (03): : 1185 - 1199
  • [34] Channel Boosting Feature Ensemble for Radar-based Object Detection
    Azam, Shoaib
    Munir, Farzeen
    Jeon, Moongu
    2021 32ND IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2021, : 762 - 769
  • [35] Radar-based evaluation of lameness detection in ruminants: preliminary results
    Fioranelli, Francesco
    Li, Haobo
    Le Kernec, Julien
    Busin, Valentina
    Jonsson, Nicholas
    King, George
    Tomlinson, Martin
    Viora, Lorenzo
    2019 IEEE MTT-S INTERNATIONAL MICROWAVE BIOMEDICAL CONFERENCE (IMBIOC 2019), 2019,
  • [36] MOTION-TOLERANT RADAR-BASED HEART SOUND DETECTION
    Rong, Yu
    Han, Kawon
    Lenz, Isabella
    Bliss, Daniel W.
    2024 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, ICASSP 2024, 2024, : 2185 - 2189
  • [37] Radar-based Detection of Bats: Experiments in a Laboratory Flight Tunnel
    Moll, Jochen
    Maelzer, Moritz
    Scholz, Nikolas
    Krozer, Viktor
    Pozdniakov, Dimitry
    Salman, Rahmi
    Zimmermann, Ralph
    Hechavarria, Julio
    Beetz, M. Jerome
    Koessl, Manfred
    2016 10TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), 2016,
  • [38] Feasibility of Radar-Based Detection of Floating Macroplastics at Microwave Frequencies
    Felicio, Joao M.
    Costa, Tomas S.
    Vala, Mario
    Leonor, Nuno
    Costa, Jorge R.
    Marques, Paulo
    Moreira, Antonio A.
    Caldeirinha, Rafael F. S.
    Matos, Sergio A.
    Fernandes, Carlos A.
    Fonseca, Nelson J. G.
    de Maagt, Peter
    IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2024, 72 (03) : 2766 - 2779
  • [39] Multiple Test Procedures for radar-based detection of buried landmines
    Brunzell, Hakan
    Zoubir, Abdelhak
    Conference Record of the Asilomar Conference on Signals, Systems and Computers, 1999, 2 : 831 - 834
  • [40] Machine Learning Methods for Radar-Based People Detection and Tracking
    Castanheira, Jose
    Curado, Francisco
    Tome, Ana
    Goncalves, Edgar
    PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2019, PT I, 2019, 11804 : 412 - 423
12345